With the success of the Internet and growing network resources, audio and video streaming is of enormous interest among Internet multimedia applications. Recently, tools such as RealPlay™ software and Microsoft NetShow® software have been developed to stream media content over a network. There remain, however, challenges to the streaming of media over the IP-based Internet due to issues such as the lack of a quality of service (QoS) guarantee, bandwidth variations, packet-losses, delays varying from time to time, and unknown network characteristics.
Since the Internet is a shared environment and does not micro-manage utilization of its resources, end systems are expected to be cooperative by reacting to congestion properly and promptly. As a result, overall utilization of the network remains high while each flow obtains a fair share of resources. Unfortunately, many of the current commercial streaming applications do not behave in a network-friendly fashion.
The available bandwidth in the Internet fluctuates frequently in nature. Most conventional streaming applications are unable to perform quality adaptation as available bandwidth changes, especially quality adaptation among multiple streams. Thus, these conventional streaming applications do not make effective use of the bandwidth.
To date several schemes have been developed for QoS management such as resource reservation, priority mechanism, and application level control. Prior art QoS management schemes and other background information, referred to elsewhere in the document, are presented in the following publications, each of which is incorporated herein by reference in entirety:
1. R. Braden, L. Zhang, S. Berson et al, “Resource ReSerVation Protocol (RSVP)—Version 1 Functional Specification”, RFC2205, September 1997 (“hereinafter, “Braden et al.”);
2. R. Rejaie, M. Handley, and D. Estrin, “Quality adaptation for congestion controlled video playback over the Internet”, Proceedings of SIGCOM 99 (“hereinafter, “Rejaie et al. [SIGCOM]”);
3. R. Rejaie, M. Handley, and D. Estrin, “An end-to-end rate-based congestion control mechanism for realtime streams in the Internet”, Proceedings of INFOCOMM 99, 1999 (“hereinafter, “Rejaie et al. [INFOCOMM]”);
4. T. Chiang and Y. Q. Zhang, “A new rate control scheme using quadratic rate-distortion modeling”, IEEE Trans. Circuits Syst. Video Technol., February 1997 (“hereinafter, “Chiang et al.”);
5. D. Sisalem and H. Schulztinne, “The loss-delay based adjusted algorithm: A TCP-friendly adaptation scheme”, Proceedings of NOSSDAV'98, 1998 (“hereinafter, “Sisalem et al.”);
6. J. Padhye, V. Firoiu, D. Towsley and J. Kurose, “Modeling TCP throughput: A simple model and its empirical validation”, Proceedings of SIGCOMM'98, 1998 (“hereinafter, “Padhye et al.”);
7. O. Verscheure, P. Frossard and M. Hamdi, “MPEG-2 video services over packet networks: joint effect of encoding rate and data loss on user-oriented QoS”, Proceedings of NOSSDAV 98, 1998 (“hereinafter, “Verscheure et al.”);
8. A. Vetro, H. F. Sun and Y. Wang. “MPEG-4 rate control for multiple video objects”. IEEE Trans. Circuits Syst. Video Technol., February 1999 (“hereinafter, “Vetro et al.”); and
9. M. Eckert and J. I. Ronda. “Bit-rate allocation in multi-object video coding”. ISO/IEC JTC1/SC29/WG11 MPEG98/m3757, Dublin, Ireland (“hereinafter, “Eckert et al.”).
Among the foregoing QoS management schemes, resource reservation for supporting a certain QoS level, which was proposed by Braden et al., is the most straightforward approach. However, since it is difficult to know the characteristics of a stream in advance, one may tend to over-allocate resources in order to guarantee the requested QoS level, leading to network under-utilization. Besides that, the most challenging issue for the resource reservation mechanism is that it is both difficult and complex to implement and to deploy.
In priority mechanisms, different data packets or streams are labeled with different priorities and thereby treated differently at the network routers. While this approach is simple, the exact mechanism for setting the priority levels, the router mechanism for controlling these levels, and the actual gain are unclear.
In application level control scheme, the QoS is controlled by adapting the sender transmission rate as was taught by Rejaie et al. [SIGCOM] and Chiang et al. Most of the control algorithms, however, randomly distribute resources among multiple streams without a global coordination mechanism. In order to employ a global coordination scheme, traffic control is usually adopted. There are several TCP-friendly rate adjustment protocols that have been reported recently. It has been proposed that transport protocols, including those taught by Rejaie et al. [INFOCOMM] and Sisalem et al. who teach transport protocols where the throughput of a long-lived TCP connect is calculated based on the TCP characterization. However, Padhye et al. demonstrated that the above approaches to calculating the throughput are not accurate in cases where the packet-loss rate is higher than five percent (5%). Since this approach does not account for retransmission timeouts, it usually overestimates the throughput of a connection as the packet-loss rate increases.
Other challenges to streaming video include network bandwidth adaptation, media adaptation, and error resilience. Network bandwidth adaptation deals with dynamic network bandwidth estimation, while media adaptation controls the media bit rate according to the network conditions. Error resilience refers to the ability to track, localize and recover transmission errors.
Without bandwidth adaptation, video transmission tends to compete unfairly with other TCP traffic, causing network congestion and resulting in a lower transmission rate for other TCP traffic. In addition, congestion collapse occurs when the aggregate bandwidth of the media traffic exceeds the network capacity. In order to dynamically adjust the transmission rate while co-existing with other TCP-based applications, several congestion control protocols have been proposed to adapt the sending rate in such a way that congested bandwidth is shared “fairly” with TCP applications. The majority of these protocols are based on TCP characterizations. Specifically, in the absence of retransmission time-outs, the steady state throughput of a long-lived TCP connect is given by:
                              Throughput          =                      C                          R              *                              p                                                    ,                            (        1        )            where C is a constant that is usually set to either 1.22 or 1.31, depending on whether the receiver uses delayed acknowledgments, R is the round trip time experienced by the connection, and p is the expected number of window reduction events per packet sent. Since Equation (1) does not account for retransmission timeouts, it usually overestimates the connection throughput as packet-loss rate increases. It is has been reported that Equation (1) is not accurate for packet-loss rates higher than 5%.
MPEG-4 is an object-based coding standard in which a visual scene typically has several video objects (VOs), each characterized by its shape, motion, and texture. The VOs are coded into separate bit streams that can be individually accessed and manipulated. The composition information is sent in a separate stream. To date several prior art rate control algorithms have been proposed. One such rate control algorithm was proposed by Chiang et al. for a single VO using a quadratic rate-quantizer model as the baseline rate control scheme used in the MPEG4 standard. This rate control scheme was extended by Vetro et al. to multiple video objects (MVOs). As taught by both Chiang et al. and Vetro et al., the total target bit rate for all objects is controlled by a “joint-buffer” and allocated proportionally to the motion, size, and square of MAD (mean absolute distortion). For MVOs, Eckert et al. taught several straightforward approaches based upon the video object importance level. Although these approaches allow different objects to be encoded at different frame rates, when put in one scene, these objects with different frame rates may cause a break in the composition information and can result in unacceptable video reconstruction.
When MPEG-4 video is transported over the Internet, all the above rate control schemes could not work well since they do not adapt to network bandwidth and packet-loss conditions that vary from time to time. Thus, the available resources could not be efficiently utilized and sometimes they may suffer from heavy congestion.
It would be an advance in the art to devise a multimedia streaming TCP-friendly transport protocol that can adaptively estimate the network bandwidth and smooth the sending rate. It would also be an advance in the art to devise a global resource allocation control mechanism that maximizes the quality of AV streams delivered across fairly congested connections, where bits are allocated dynamically according to the media encoding distortion and network degradation. With respect to multiple video objects, it would be an advance in the art to devise a rate control scheme that uses such a multimedia streaming TCP-friendly protocol while minimizing the overall distortion under the constraint that the total rate for all objects is upper-bounded by a target bit rate. Finally, an advance in the audiovisual streaming art would be achieved by minimizing the end-to-end distortion for a given network traffic condition and picture quality requirement.